GOAT: Development of a Wireless Sensor Network analysis tool

Bachelor’s Degree Thesis Director: Boris Bellalta UPF (Barcelona), July 15th 2015

Sergio Barrachina Muñoz

OUTLINE

•  Introduction •  Wireless Sensor Networks

–  Architecture and components –  Applications –  Challenges

•  GOAT –  What is GOAT? –  Architecture and Design –  Graphical User Interface (GUI) –  Modules –  Operation

•  Evaluation –  Smart parking –  Plague tracking

•  Conclusions and future work

1.1 What is a WSN?

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WSN overall architecture (Source: own elaboration)

1.2 Problem and objectives

•  The problem –  WSN are composed of tiny devices (small batteries) –  Energy-constrained designs –  Goal: To maximize the network lifetime while still providing

appropriate QoS requirements

•  Project objectives –  Develop a WSN analyzer

l  Design l  Thoroughly configurable WSN scenarios l  Estimate energy consumption and network lifetime

–  Proof of concept: Analyze two abstractions of real WSN scenarios

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2 WIRELESS SENSOR NETWORKS

Wireless Network Solutions (Source: www.motorola-latinamerica.hosted.jivesoftware.com)

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2.1 Architecture and components

•  Components

Sensor nodes1 Gateways2 Software3

1.  Libelium waspmote (Source: http://www.libelium.com/uploads/2013/02/waspmote_pro-400px.jpg) 2.  WSN gateway WSDA (Source: http://orcom.com.ua/en/cat/19/9212/) 3.  NI LabView 2011 Silver Controls (Source: http://www.ni.com/white-paper/12892/es/)

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2.1 Architecture and components

•  Sensor vs. Sensor node

1.  Temperature sensor (Source: https://www.sparkfun.com/products/10988) 2.  Sound sensor (Source: http://imall.itead.cc/im120710013.html) 3.  Light sensor (Source: https://www.controlanything.com/Relay/Device/PDV-P8001) 4.  Shield Xbee (Source: http://www.geekfactory.mx/tienda/shield-para-xbee-y-sensores/)

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Sens

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Sensor node

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2.1 Architecture and components

WSN and sensor node architectures (Source: own elaboration) 6/30

2.2 Applications

•  Agriculture monitoring •  Air pollution monitoring •  Forest fire detection •  Industrial monitoring •  Medical care •  Plague tracking •  Smart cities •  Smart home monitoring •  …

“The impact of WSNs in the world can rival the

impact the Internet has had in the past.”

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2.3 Challenges

•  Different systems (Zigbee, 802.15.4, BLE…) –  None has prevailed due to the complexity and diversity of

applications and environments à standard de facto missing •  Power consumption •  Other

–  Architecture –  Dynamic environmental conditions –  Unattended operation –  Hardware cost –  Wireless connectivity –  Programmability –  Security

Technological obstacles and energy constraints make

WSNs a fascinating field of study

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3. GOAT

GOAT Graphical User Interface (Source: own elaboration) 9/30

1. GOAT logo (Source: own elaboration)

3.1 What is GOAT?

•  What is GOAT –  Graphical WSN planning tool –  Compatible with Windows, Mac OS and Linux kind OSs

l  Only Java JDK 7.0 or above is required –  Allows WSN designers to evaluate the effect of several

models –  Is aimed to be an open source project (modularity) –  Fields of use: educational, research and business

•  Main goal –  Running real experiments on WSN testbeds is costly and

challenging –  GOAT: Base future WSN designs on simulation results

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3.2 Architecture and design

GOAT functional design (Source: own elaboration) 11/30

3.2 Architecture and design

1. UML class diagram (Source: own elaboration) 2. RoutingModel.java UML (Source: own elaboration)

•  Technical design –  Fully written in Java –  Netbeans 8.0.2 IDE –  Java packages:

l  .awt l  .swing

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3.3 Graphical User Interface

1.  GOAT Graphical User Interface (Source: own elaboration) 2.  Informational and error messages displaying (Source: own elaboration) 3.  Random topology generation pop-up window (Source: own elaboration)

•  Design –  Intuitive functionality (ease of learning) –  Simplicity – Ease of remembering –  Follow common patterns –  Use metaphors –  Monochromatic backgrounds

l  Keep focus –  Lou user error rate –  Pop-up windows –  Drag & Click listeners

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3.3 Graphical User Interface

•  Structure

Map1 Components2

1. GUI Map (Source: own elaboration) 2. GUI Components (Source: own elaboration) 14/30

3.4 Modules

•  I. Physical –  Radio propagation models to determine if a

node can be reached from another one. –  Models

l  Free space (Friis) l  Log-normal fading

•  II. Battery –  Node battery charge to determine the energy

stored in a node. –  Models

l  2x AAA (1,500 mAh) l  Lithium battery (2,200 mAh) l  2x AA (7,500 mAh)

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1. Free space propagation model equation 2.  AA batteries (Source: http://rightbattery.com/1-5v-aa-duracell-alkaline- battery.jpg) 15/30

3.4 Modules

•  III. Medium Access Control (MAC) –  Make possible that several nodes

communicate over a shared channel. –  Models

l  B-MAC l  B-MAC/ACK l  IEEE 802.11ah

–  Node states l  Transmitting l  Receiving l  Sampling the channel l  Sleeping

1.  Node’s transmitting time during an observation time on B-MAC, B-MAC/ACK, and 802.11ah 2.  Energy consumed by a node during an observation time 3.  Node’s lifetime in time units

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3.4 Modules

•  IV. Routing –  Defines which wireless links will be created to allow any

sensor node reaching the sink depending on several conditions –  Coverage –  Quality of service (QoS) –  Energy saving mechanisms –  …

–  Models –  Single-hop –  Next-node –  Closest-node (Power based)

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1. Routing levels (Source: own elaboration) 17/30

3.4 Modules

Single-hop1 Closest-node3

1.  Single-hop routing example (Source: own elaboration) 2.  Next-node routing example (Source: own elaboration) 3.  Closest-node routing example (Source: own elaboration)

Next-node2

Routing models

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3.5 Operation

•  I. Topology design

1.  WSN topology design without sink defined (Source: own elaboration) 2.  WSN topology with sink defined (Source: own elaboration)

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3.5 Operation

•  II. Configuration –  Packet generation rates –  Modules –  Hard-coded variables

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1.  Packet generation rate pop-up window (Source: own elaboration) 2.  Modules components section (Source: own elaboration) 3.  Caption of hard-coded variables of MacModel.java class (Source: own elaboration)

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3.5 Operation

•  III. Simulation

GOAT simulation process diagram (Source: own elaboration) 22/30

4. EVALUATION

•  Evaluate two abstractions of feasible scenarios –  Objectives

l  Test GOAT l  Proof of concept

–  Scenarios l  Smart parking

–  Based on the SMART SANTADER PROJECT –  Juan de Garay Street, Barcelona –  Detect public parking sites availability

l  Plague tracking –  Based on the ENTOMATIC project –  Olive tree field placed near El Barranc de la Punta, Tarragona –  Detect and control olive tree fly population

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4.1 Smart parking

•  Scenario definition

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1.  Smart parking scenario (Source: own elaboration) 2.  Parking sensor and repeater (Source: http://www.libelium.com/smart_santander_smart_parking/) 24/30

4.1 Smart parking

•  Modeling and results –  Compare routing and sink location –  Optimal implementation

l  MAC model: B-MAC l  Routing model: Closest-node l  Sink: Node 7

Sink Overall lifetime [days]

Node 25 123.82

Node 8 124.72

Node 23 124.72

Node 7 127.38

Node 22 126.64

1.  Overall WSN lifetime depending on the sink location (Source: own elaboration) 2.  Smart parking final design (Source: own elaboration)

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4.2 Plague tracking

•  Scenario definition

1.  Plague tracking scenario (Source: own elaboration) 2.  Bactrocera oleae (Source: http://fitolea.blogspot.com.es/)

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4.2 Plague tracking

•  Modeling and results –  58 ha rectangular area –  5 nodes/ha –  Compare models

l  Battery l  Physical l  MAC

–  Determine the required number of sinks

–  Optimal implementation l  Battery: x2 AA l  PHY: Free space l  MAC: 802.11ah l  Routing: Single-hop

MAC model B-MAC B-MAC/ACK 802.11ah

Overall lifetime 110.96 days 109.22 days 152.38 days

1.  Network lifetime depending on the battery model (Source: own elaboration) 2.  Area sectoring for log-normal γ = 2.2 and log-normal γ = 2.5 (Source: own elaboration) 3.  MAC model impact on lifetime (Source: own elaboration)

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Battery model x2 AAA (1500 mAh) Lithium (2200 mAh) x2 AA (7500 mAh)

Network lifetime 30.47 days 44.69 days 152.38 days

5. CONCLUSIONS AND FUTURE WORK

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Summary artwork (Source: http://propertyupdate.com.au/)

5.1 Future work

•  Improve the analyzer –  Allowing full parameters configuration from the GUI –  Including packet collisions to improve results

accuracy –  Finding automatically the optimal sink position –  Improve the GUI design

•  Share the project –  Ensure the code is idiomatic and follows best

practices –  Divulge and promote collaboration –  Determine software legal and property issues

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1. Caption of the GOAT article presented to MACOM 2015 (Source: own elaboration) 29/30

5.2 Conclusions

•  WSNs will change the way we understand communications

•  Top constraint: Limited energy resources of sensor nodes –  Objective: To reduce energy consumption à extend lifetime –  Problem: Testing designs and protocols is required but costly

•  GOAT is a graphical WSN analyzer –  Design WSN and estimate its energy consumption –  Several deeply configurable models (PHY, MAC, and routing) –  Open source project –  As a first version the tool can be enhanced in several aspects

•  Major learning experience for me –  Delve deep into software design and Java programming –  Hone my knowledge about WSN

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Thank you for your attention